## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", dev = "png", # fig.path = "figures/viz-", fig.height = 5, fig.width = 7 ) ## ----packages, message = FALSE, warning = FALSE------------------------------- # Load relevant packages library(tscv) library(tidyverse) library(tsibble) ## ----abbreviations, echo=FALSE, warning=FALSE, message=FALSE, results='hide'---- Sys.setlocale("LC_TIME", "C") ## ----data--------------------------------------------------------------------- series_id = "bidding_zone" value_id = "value" index_id = "time" context <- list( series_id = series_id, value_id = value_id, index_id = index_id ) # Prepare data set main_frame <- elec_price %>% filter(bidding_zone %in% c("DE", "FR", "NO1", "SE1")) main_frame ## ----plot_line, fig.alt = "plot_line"----------------------------------------- # Example 1 ------------------------------------------------------------------- main_frame %>% plot_line( x = time, y = value, color = bidding_zone, facet_var = bidding_zone, title = "Day-ahead Electricity Spot Price", subtitle = "2019-01-01 to 2020-12-31", xlab = "Time", ylab = "[EUR/MWh]", caption = "Data: ENTSO-E Transparency" ) # Example 2 ------------------------------------------------------------------- main_frame %>% plot_line( x = time, y = value, color = bidding_zone, title = "Day-ahead Electricity Spot Price", subtitle = "2019-01-01 to 2020-12-31", xlab = "Time", ylab = "[EUR/MWh]", caption = "Data: ENTSO-E Transparency" ) ## ----plot_bar, fig.alt = "plot_bar"------------------------------------------- # Estimate sample partial autocorrelation function corr_pacf <- estimate_pacf( .data = main_frame, context = context, lag_max = 30 ) corr_pacf # Visualize PACF as correlogram corr_pacf %>% plot_bar( x = lag, y = value, color = sign, facet_var = bidding_zone, position = "dodge", title = "Sample autocorrelation function", xlab = "Lag", ylab = "Correlation", caption = "Data: ENTSO-E Transparency" ) ## ----plot_histogram, fig.alt = "plot_histogram"------------------------------- # Example 1 ------------------------------------------------------------------- main_frame %>% plot_histogram( x = value, color = bidding_zone, title = "Day-ahead Electricity Spot Price", xlab = "[EUR/MWh]", ylab = "Frequency", caption = "Data: ENTSO-E Transparency" ) # Example 2 ------------------------------------------------------------------- main_frame %>% plot_histogram( x = value, color = bidding_zone, facet_var = bidding_zone, facet_nrow = 1, title = "Day-ahead Electricity Spot Price", xlab = "[EUR/MWh]", ylab = "Frequency", caption = "Data: ENTSO-E Transparency" ) ## ----plot_density, fig.alt = "plot_density"----------------------------------- # Example 1 ------------------------------------------------------------------- main_frame %>% plot_density( x = value, color = bidding_zone, title = "Day-ahead Electricity Spot Price", xlab = "[EUR/MWh]", ylab = "Density", caption = "Data: ENTSO-E Transparency" ) # Example 2 ------------------------------------------------------------------- main_frame %>% plot_density( x = value, color = bidding_zone, facet_var = bidding_zone, facet_nrow = 1, title = "Day-ahead Electricity Spot Price", xlab = "[EUR/MWh]", ylab = "Density", caption = "Data: ENTSO-E Transparency" ) ## ----plot_qq, fig.alt = "plot_qq"--------------------------------------------- # Example 1 ------------------------------------------------------------------- main_frame %>% plot_qq( x = value, color = bidding_zone, title = "Day-ahead Electricity Spot Price", xlab = "Theoretical Quantile", ylab = "Sample Quantile", caption = "Data: ENTSO-E Transparency" ) # Example 2 ------------------------------------------------------------------- main_frame %>% plot_qq( x = value, color = bidding_zone, facet_var = bidding_zone, title = "Day-ahead Electricity Spot Price", xlab = "Theoretical Quantile", ylab = "Sample Quantile", caption = "Data: ENTSO-E Transparency" )